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European control Conference (ECC)

作者： M. Guinaldo J. SánchezMoreno S. Zaragoza F. J. Mañas-Álvarez Dept. Computer Science and Automatic Control UNED Madrid Spain Centro Universitario de la Defensa San Javier Murcia Spain

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper proposes a method to recover from the failure or loss of a subset of agents in a distance-based formation problem, where the system is initially deployed forming a virtual shield embedded in the 3D space. First, a distributed algorithm is proposed to restore the topology, which is a Delaunay triangulation. After that, the nodes execute a distance-based distributed control law that considers adaptive target distances. These values are computed in parallel by the nodes, which try to reach an agreement with some constraints, given by the desired shield shape. The updating policy is based on events. The results are illustrated through simulation examples.

关键词： Three-dimensional displays Shape Decentralized control Europe Aerospace electronics Topology Distributed algorithms

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Predicting the Time from Diagnosis to Treatment in Breast Cancer

Predicting the Time from Diagnosis to Treatment in Breast Ca...

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E-Health and Bioengineering Conference (EHB)

作者： Sergiu Ceică Ştefan-Daniel Achirei Dept. of Computer Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iasi Iasi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Recent advancements in machine learning (ML) have significantly impacted the medical field, particularly in diagnosing and treating breast cancer. This study models the time from diagnosis to treatment for breast cancer patients, focusing on delay factors and ML-based solutions. The goal is to develop precise ML models that predict treatment delays, thereby improving the quality and efficiency of medical services. We investigated socio-economic disparities affecting treatment access and developed models to predict these delays. The predictive models used include K-Nearest Neighbors, Decision Trees, Linear Regression, and Boosting Algorithms such as AdaBoost and Gradient Boosting Regressor. By accurately predicting the interval from diagnosis to the first treatment, our work aims to promote equity in healthcare, ensuring timely treatment for all patients. Our findings highlight the potential of ML in optimizing treatment timelines and resource allocation, contributing to improved patient outcomes and advancing the medical system.

关键词： Medical services Predictive models Boosting Prediction algorithms Breast cancer Delays Resource management Socioeconomics Medical diagnostic imaging Regression tree analysis

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Remaining Useful Life Prediction of Multi-Component System Clustering with Time-Varying Kernel Density

Remaining Useful Life Prediction of Multi-Component System C...

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2023 China Automation Congress, CAC 2023

作者： Li, Ke Fan, Xingle Shi, Hui Zhang, Xiaohong Sun, Chaoli Wang, Jianan Taiyuan University of Science and Technology Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Dept. of Electronic and Information Engineering Taiyuan China Taiyuan University of Science and Technology Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Dept. of Economics and Management Taiyuan China Taiyuan University of Science and Technology Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Dept. of Computer Science and Technology Taiyuan China

ISBN: (纸本)9798350303759

Aiming at the uncertainty of the degradation procedure of a complex multi-component system in a time-varying environment and the influence of the random dependence between different components, a remaining useful life prediction model for time-varying adaptive kernel density estimation based on the dependence between multiple components is established. First, the random dependence between multi-component systems is clustered. Considering that different components in the same cluster are affected by the random dependence, the components between different clusters do not affect each other. Judge the dependence characteristics between components, and use the dependence characteristics of different components to conduct clustering degradation modelling. Secondly, the parameters of the system change with time. Considering that monitoring data near the current time has a greater impact on the remaining useful life prediction compared with historical data, data in the vicinity of the current time is accorded a more significant weight, and a time-varying kernel density estimation prediction method is designed, in which the nearest-neighbour adaptive window-width selection method is used. Finally, give an example to demonstrate the effectiveness by the proposed method. © 2023 IEEE.

关键词： Forecasting

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COMPARING WSN PERFORMANCE: TRADITIONAL VS. SDN APPROACH

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2024年第4期86卷 81-94页

作者： Hamad, Diyar Jamal Yalda, Khirota Gorgees Okumus, Ibrahim Taner Tapus, Nicolae Faculty of Automatic Control and Computer Science University of Science and Technology POLITEHNICA Bucharest Soran Technical college Erbil Polytechnic University Erbil Iraq Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey Dept. of Computer Science University of Science and Technology POLITEHNICA Bucharest Romania

The proliferation of Wireless Sensor Networks (WSN) in various applications has necessitated the exploration of network architectures that can ensure efficient, scalable, and reliable communication. This study presents a comparative performance evaluation of traditional networking paradigms and Software-Defined Networking (SDN)-based architectures within WSN. Utilizing the Floodlight SDN controller and Mininet-WiFi emulator, we conducted a series of experiments across three different network topologies, varying the number of hosts and access points. The performance metrics focused on are average latency, packet loss percentage, and throughput. The results demonstrate a considerable improvement in all measured parameters under the SDN-based environment compared to the traditional setup. Specifically, SDN environments consistently showcased lower latency, minimal packet loss, and higher throughput, with the most notable difference observed in smaller network configurations. The findings suggest that SDN, with its centralized control plane, can significantly enhance the performance of WSNs, particularly in scenarios demanding rapid scalability and dynamic traffic management. This study underscores the potential of SDN architectures in optimizing WSN operations and lays the groundwork for future research in this domain. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Floodlighting

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Automated Assessment of Medical Rehabilitation of Gait by Means of Video Processing in Cloud Environment

Automated Assessment of Medical Rehabilitation of Gait by Me...

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E-Health and Bioengineering Conference (EHB)

作者： Elena-Claudia Maftei Otilia Zvorişteanu Hariton-Nicolae Costin Silviu Bejinariu Florin Rotaru Vasile Manta Ramona Luca Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Institute of Computer Science Romanian Academy Iaşi Branch Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Human gait analysis provides qualitative and quantitative information concerning different characteristics of walking of a certain person. Cloud computing proves to be a modern and valuable technology when dealing with data scalability, security and efficiency of processing and storage. Also, this paradigm has some key-benefits like real-time data sharing, fast computation as well as collaborative research. The applications gamut which uses cloud computing is getting bigger and bigger, and healthcare sector is an important domain in this respect. Our approach proposed a cloud-based service designed for the automated assessment of medical rehabilitation of human gait by using video processing. We have chosen this processing technology because it is marker-less, allows fast computation and offers a very good precision of the gait analysis. Cloud computing approach proved to be encouraging and underscores remarkable advantages in comparison with traditional on-site video processing. In this way the patient, after a short training session, can himself/herself make tests and assessments of his/her mobility status, avoiding many consultations of medical or kineto-therapeutic staff.

关键词： Legged locomotion Training Cloud computing Scalability Medical services Gain measurement People with disabilities Real-time systems Security Personnel

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Efficient Deep Learning Models Based on Tension Techniques for Sign Language Recognition

SSRN

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SSRN 2023年

作者： Attia, Nehal F. Faheem Said Ahmed, Mohamed T. Alshewimy, Mahmoud A.M. Computer and Automatic Control Dept. Faculty of Engineering Tanta University Tanta Egypt

Among the various ways of self-expression and communication between people, communication by speaking prevails. Speech presents a significant challenge for some disabled people, such as the deaf, hearing impaired, wordless, and dumb persons. Therefore, these people rely on the use of sign language to interact with others. Sign language is a system of movements and visual messages that ensure the integration of these individuals into groups that communicate vocally. On the other side, it is necessary to understand the gestures and linguistic semantics of these individuals. The main objective of this study is to establish a new model that enhances the performance of the existing paradigms in use for the recognition of American Sign Language (ASL). Therefore, three enhanced deep-learning models of YOLOv5 for recognizing the alphabetic and numeric information conveyed by hand motions are presented in this paper. These models depend on using different attention approaches. The suggested models were evaluated using the MU HandImages ASL dataset. The proposed models yielded superior results compared to those achieved by the initial version of YOLOv5. The modified models have reached their maximum accuracy of 98.9%, maximum recall of 97.5%, maximum mAP 0.5 of 99.2%, and maximum mAP 0.5:0.95 of 98.9%. © 2023, The Authors. All rights reserved.

关键词： computer vision

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Advancing Environmental Sustainability: Renewable Energy Transition, Carbon Footprint Reduction, and Emission control Innovations 22

Advancing Environmental Sustainability: Renewable Energy Tra...

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22nd International Learning and Technology Conference, L and T 2025

作者： Hussein, Aziza I. Alghamdi, Roba W. Al-Amoudi, Amal Abdullah Altahawi, Omar Hisham Kabbaja, Narjisse Mabrook, Mohamed Mourad Lotfy, Mostafa Wageh Effat University Electrical & Computer Eng. Dept. Jeddah Saudi Arabia Beni-Suef University Faculty of Navigation Science & Space Technology Space Communication Dept. Beni-Suef Egypt Beni-Suef University Faculty of Technology and Education Dept. of Process Control Technology Beni-Suef Egypt

ISBN: (纸本)9798331532215

Combating climate change and promoting environmental sustainability necessitate a dedicated emphasis on renewable energy sources and lowering carbon footprints. Shifting from fossil fuels to renewable resources, such as solar, wind, biomass, and geothermal energy, is imperative. Equally important is enhancing energy efficiency across industries, transportation, buildings, and household appliances to reduce overall energy consumption and greenhouse gas emissions. Technological advancements, such as improved energy storage and smart grid systems, are essential for boosting the efficiency and dependability of renewable energy sources. Strategies to lower carbon footprints include transitioning to clean transportation, optimizing land use, reducing waste, recycling, promoting sustainable agriculture, and implementing carbon offset initiatives. Public education, corporate responsibility, and personal environmental awareness play vital roles in supporting carbon reduction. By combining sustainable energy practices with carbon reduction measures, we can collectively work towards curbing climate change and fostering a sustainable future. Additionally, utilized techniques to address the problem of high air pollution during vehicle cold starts. We modeled catalytic converter dynamics in MATLAB Simulink, using simplifying assumptions. One significant assumption involved treating the catalytic converter as a Continuous Stirred-Tank Reactor (CSTR), which allowed us to model its temperature uniformly, without accounting for temperature changes along its length. This approach is aimed at saving lives and reducing costs by effectively minimizing air pollution. © 2025 IEEE.

关键词： Clean energy

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A COMPARATIVE STUDY OF SUPPORT VECTOR MACHINE AND RISK DETERMINISTIC APPROACH ON A PHOTOVOLTAIC SYSTEM

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2024年第3期86卷 67-80页

作者： Colbu, Ștefania-Cristiana Băncilă, Daniel-Marian Petrescuniță, Alina Popescu, Dumitru Olteanu, Severus-Constantin Dept. of Automatic Control and Systems Engineering National University of Science and Technology POLITEHNICA Bucharest Romania Dept. of Mathematical Methods and Models National University of Science and Technology POLITEHNICA Bucharest Romania

The present paper introduces a comparative analysis of the management of a stochastic optimization problem using both a risk deterministic approach and a support vector machine strategy. This optimization problem is formulated in consideration of the influence produced by environmental factors, such as irradiance and temperature, on a photovoltaic panel. The problem will be solved by applying both methods to determine the Maximum Power Point (MPP), thereby to enhance the power generation efficiency. The primary objective is to conduct an analysis comparing the two approaches, with the aim of recommending the most suitable approach for Maximum Power Point Tracking (MPPT). © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： machine learning photovoltaics risk optimization support vector machine for regression

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Multi-layer network modelling of genomic and transcriptomic data to investigate the response to checkpoint inhibitors in NSCLC

Multi-layer network modelling of genomic and transcriptomic ...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Mascolo, Davide Farina, Lorenzo Petti, Manuela Sapienza University of Rome Program in Data Science Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350337488

Recent innovations and developments in molecular biology and biotechnology have made it possible to acquire and store large omics datasets. In particular genomics, transcriptomics and the study of their relationship represent the key elements to understand how genotype influences phenotype. In this work we investigate the potential of multi-layer network modeling in integrating genomic and transcriptomic data of 152 advanced non-small cell lung cancer (NSCLC) patients treated with anti-PD-(L)1 therapy. For the transcriptomic layer, we performed differential expression and differential co-expression analyses in order to identify a subset of key genes in differentiating responder patients from non-responders. Adding to the genomic-transcriptomic model other three layers related to immune, myeloid and curated immunotherapy-based literature signatures we obtained a 5-layer Patient Similarity Network. The application of Similarity Network Fusion algorithm revealed a statistically significant stratification of patients (p-value ≤ 0.05) which allows the identification of two clusters characterized by patients responding and not responding to immunotherapy. © 2023 IEEE.

关键词： immunotherapy multi-layer network Network-based omics integration non-small cell lung cancer patient Stratification

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The All Wheel Speed Balance control Concept 27

The All Wheel Speed Balance Control Concept

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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Atheupe, Gael P. Martinez, Didier Monsuez, Bruno Renault Technical Centre Renault Group & Ensta Paris Paris France Renault Technical Centre Renault Group Dept. Chassis Control & Adas Systems Guyancourt France Ensta Paris Dept. Computer Science & Systems Engineering Paris France

ISBN: (纸本)9798331505929

The transition to vehicle electrification introduces new demands on chassis dynamics, paving the way for advances in driving dynamics, safety, and efficiency. A key consideration arises: how are driving torque impulses converted in electric vehicles with multiple power sources? This study introduces a novel approach to address these demands through the integration of state-of-the-art yaw control, using concurrent front/rear axle and front right/front left torque distribution based on the wheel speed balance control concept. Our aim is not necessarily to demonstrate the supremacy of our approach, but rather to present a fresh philosophical perspective on the problem of yaw control in electric vehicles. Our method embodies dynamic load transfer and axle dynamics into the yaw control problem formulation, setting it apart from current methodologies. Through experimental results, we illustrate the effectiveness of our proposed approach regardless of road surface conditions. © 2024 IEEE.

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